… of machine learning, deep learning has shown potential in data feature extraction and pattern
recognition. Because of its excellent ability in data analysis and prediction… load forecasting; …

… comparison of charging load prediction result by traditional k-means clustering with that by
consensus k-means clustering (at financial centre charging … heterogeneous electric vehicle …

… Charging pile load prediction based on deep learning quantile regres⁃ sion model[J].
Power … Mid-and long-term charging load forecasting for electric vehicles in residential areas …

… methods for Lithium-ion batteries in electric vehicles is … A comparative study of equivalent
circuit models and enhanced … Advanced machine learning approach for lithium-ion battery …

… level short-term load forecasting using deep neural networks[C]… A bottom-up short-term
residential load forecasting approach … and load forecasting of household electric vehicle charging …

… Research review on power load forecasting methods in distribution network … load forecasting
of power system considering demand response and multi-task learning based on deep …

… Review of the short-term load forecasting methods of electric power system[J]. Power …
Application of Gaussian process machine learning to the prediction of groundwater level[J]. China …

… In particular, aggregated charging load of electric vehicles cause overload in the distribution
… In the study in [64], a comparative analysis was made with three different approaches. The …

… Multitime-scale electric vehicle load forecasting model consid⁃ ering seasonal characteristics[J].
… Charging load forecasting for large-scale electric vehicle[J]. Pow⁃ er Demand Side …